Memory loss affects a significant number of people. There are several strategies and tools to cope with this disorder and lengthen the patients’ independence. Some of these include adaptations to their physical environment, such as placing labels on drawers or removing cabinet doors to make items visible. Other more sophisticated tools use computing devices.

Existing tools use a variety of technologies to display information to users; however, they have certain limitations, since they can’t display spontaneous information, i.e. with\-out specifying a time and date to send the user a reminder or show some message. There are computer vision techniques used to recognize items in the environment, such as visual markers, however, they cause unwanted visual disorder and a marker needs to be placed on each object or location of interest.

This thesis proposes the ANS, an ambient annotation system focused on assisting people with memory problems and their caregivers. This system is aimed at indoor environments and includes three major subsystems: (1) Tag Manager, used for creating, editing, and deleting tags, (2) the Server application, responsible for calculating the user’s location at a room level and performing the tag search in the environment, and (3) the Client application running on a mobile device, which notifies the user about tags in the environment and presents their associated information (text, audio or images).

The tag identification is done in real time, sending pictures from a mobile device to a server, which uses the SURF algorithm for object recognition. The user’s location is used to reduce the tag search space; this location is calculated using the same algorithm.

We evaluated the ANS to analyze its performance in conditions similar to those expected for the target user. Among other things, we determined that audio notifications are more effective than vibrating notifications to notify the user about tags in the environment.

This thesis describes the ANS design, implementation and evaluation.
